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complicated systems. These include humanoids, quadrupeds, omnidirectional drones and others. These controllers will rely on principles like Reinforcement Learning (RL), Model Predictive Control (MPC), or other
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control (MPC) under uncertainty for autonomous systems. The research aims to develop state-of-the-art numerical methods for solving challenging belief-space optimal motion planning problems and their
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complicated systems. These include humanoids, quadrupeds, omnidirectional drones and others. These controllers will rely on principles like Reinforcement Learning (RL), Model Predictive Control (MPC), or other
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before Dec 5, 2025 will receive full consideration. About the Max Planck-IAS-NTU Center The Max Planck-IAS-NTU Center (MPC) is new interdisciplinary initiative of the Max Planck Society (MPG) in Germany
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of the system to be controlled. This RL approach will be compared and contrasted with optimal control methods such as Model Predictive Control (MPC). The various control strategies developed will first be
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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Postdoctoral Research Associate, Electrical and Computer Engineering Posting Number req24051 Department Electrical and Computer Engr Department Website Link https://ece.engineering.arizona.edu/ Location Main